Insulin Sensitivity as a Model-Based Marker for Sepsis Diagnosis

No default citation style available for Eprints

[img]
Preview
PDF
Insulin Sensitivity as a Model-Based Marker for Sepsis Diagnosis.pdf - Published Version

Download (43kB) | Preview
[img] PDF
Insulin Sensitivity as a Model-Based Marker for Sepsis Diagnosis.pdf - Published Version
Restricted to Repository staff only

Download (723kB) | Request a copy

Abstract

Sepsis is highly associated with microcirculatory dysfunction, which normally results in organ failure and increased risk of death. Importantly, early goal-directed therapy observed lower mortality rates in septic shock patients compared to those assigned to standard therapy. Currently, it is almost impossible to diagnose a patient at the onset of sepsis due to the lack of real-time metrics with high sensitivity and specificity. Patient condition is mostly determined by clinician experience and observation of patient reaction to treatment. In this study, a model-based insulin sensitivity profile is used to identify the relation between individual metabolic conditions to their sepsis status. The hour-to-hour variation of insulin sensitivity is highly independent of the treatment received by the patient and may represent a metabolic status for real-time diagnosis of sepsis. The hour-to-hour variation of insulin sensitivity profile is analyzed with sepsis score calculated according to the definition provided by ACCP/SCCM. P-values of various sepsis score group are computed using Mann-Whitney test. Cumulative distribution function of insulin sensitivity shows separation between different sepsis score and more distinguishable at a higher sepsis score compared to the lower sepsis score.

Item Type: Article
Additional Information: 9th IFAC Symposium on Biological and Medical Systems BMS 2015 — Berlin, Germany, 31 August-2 September 2015
Uncontrolled Keywords: Sepsis; Insulin Sensitivity
Subjects: T Technology > TJ Mechanical engineering and machinery
Faculty/Division: Faculty of Mechanical Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 03 Dec 2015 01:45
Last Modified: 17 Jul 2019 02:52
URI: http://umpir.ump.edu.my/id/eprint/11198
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item